Vehicle damage detection method, device and equipment and storage medium

Abstract

The embodiment of the invention provides a vehicle damage detection method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence image processing. The method comprises the following steps: acquiring a damaged vehicle image, and inputting the damaged vehicle image into a trained integrated loss assessment model to obtain damaged part information; obtaining a damage position corresponding to the damaged vehicle image according to the vehicle part segmentation model; and obtaining damage information of the vehicle according to the damage position and the damage part information. Compared with a plurality of separated damage detection models in the prior art, the invention has the advantages that the corresponding damaged part information can be obtained through one-time forward processing by using the integrated damage assessment model, the occupied computing resources are greatly reduced, the consumed computing time is greatly shortened, the detection efficiency is effectively improved, and the labor cost in the vehicle damage assessment process is reduced. And the damage position corresponding to the damaged vehicle image is obtained by combining the vehicle part segmentation models, so that the damage information of the vehicle containing the positioning information can be obtained.

Description

technical field [0001] The embodiments of the present application relate to the field of artificial intelligence, and in particular to a vehicle damage detection method, device, equipment, and storage medium. Background technique [0002] It is a very important work to determine the damaged location and the degree of damage for a damaged vehicle in a traffic accident. The traditional loss assessment method relies on manual judgment, which is inefficient and prone to errors due to personal factors of the assessor. In recent years, with the development of artificial intelligence technology, artificial intelligence (AI) is the use of digital computers or digital computer-controlled machines to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. Theories, methods, techniques and application systems for good results. Some institutions have adopted methods based on computer vision (target detec...

AI Technical Summary

Problems solved by technology

[0003] However, due to complex and changeable damage scenarios, many vehicle components, and many damage forms, it is often necessary to develop more damage detection models, such as developing multiple damage detection models for sheet metal parts, glass, tires, etc. Different Damage Detection Models

The above scheme has obvious disadvantages. First, in the model training and development stage, it is necessary to prepare and label multiple damage data sets, and train and optimize multiple damage detection models separately. The process is cumbersome, the efficiency is relatively low, and more manpower and material resources are required. At the same time, because the model obtained by training can only be used for the corresponding component type, the data reuse rate is small and the robustness is poor; the second is the model deployment stage, multiple models need to consume more computing resources, and at the same time increase the scheduling Difficulty, increased costs, etc.

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